Zobrazeno 1 - 10
of 239
pro vyhledávání: '"heavy-tailed losses"'
Autor:
Bae, Taehan1 (AUTHOR) taehan.bae@uregina.ca, Quarshie, Hanson2 (AUTHOR) hdq233@uregina.ca
Publikováno v:
Mathematics (2227-7390). Dec2024, Vol. 12 Issue 23, p3718. 26p.
Autor:
Haddouche, Maxime, Guedj, Benjamin
While PAC-Bayes is now an established learning framework for light-tailed losses (\emph{e.g.}, subgaussian or subexponential), its extension to the case of heavy-tailed losses remains largely uncharted and has attracted a growing interest in recent y
Externí odkaz:
http://arxiv.org/abs/2210.00928
Autor:
Taehan Bae, Hanson Quarshie
Publikováno v:
Mathematics, Vol 12, Iss 23, p 3718 (2024)
As an extension of the (univariate) Birnbaum–Saunders distribution, the Type-II generalized crack (GCR2) distribution, built on an appropriate base density, provides a sufficient level of flexibility to fit various distributional shapes, including
Externí odkaz:
https://doaj.org/article/815adc2da8c743dabac5510edf1b883d
In this paper, we investigate the extreme-value methodology, to propose an improved estimator of the conditional tail expectation ($CTE$) for a loss distribution with a finite mean but infinite variance. The present work introduces a new estimator of
Externí odkaz:
http://arxiv.org/abs/2002.03414
We study fast learning rates when the losses are not necessarily bounded and may have a distribution with heavy tails. To enable such analyses, we introduce two new conditions: (i) the envelope function $\sup_{f \in \mathcal{F}}|\ell \circ f|$, where
Externí odkaz:
http://arxiv.org/abs/1609.09481
Autor:
Brahimi, Brahim, Kenioua, Zoubir
We use the so-called t-Hill tail index estimator proposed by Fabi\'an(2001), rather than Hill's one, to derive a robust estimator for the distortion risk premium of loss. Under the second-order condition of regular variation, we establish its asympto
Externí odkaz:
http://arxiv.org/abs/1502.05017
Publikováno v:
The Annals of Statistics, 2015 Dec 01. 43(6), 2507-2536.
Externí odkaz:
http://www.jstor.org/stable/43818859
Publikováno v:
Annals of Statistics 2015, Vol. 43, No. 6, 2507-2536
The purpose of this paper is to discuss empirical risk minimization when the losses are not necessarily bounded and may have a distribution with heavy tails. In such situations, usual empirical averages may fail to provide reliable estimates and empi
Externí odkaz:
http://arxiv.org/abs/1406.2462
Autor:
Brahimi, Brahim, Abdelli, Jihane
Publikováno v:
In Insurance Mathematics and Economics September 2016 70:135-143
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